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JJQA.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# TODO: Address all TODOs and remove all explanatory comments
+"""TODO: Add a description here."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+https://github.com/bebetterest/JJQA
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+JJQA: a Chinese QA dataset on the lyrics of JJ Lin's songs.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://github.com/bebetterest/JJQA"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = "Apache-2.0 license"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = {
+    "qa": "hf_q_a.json",
+    "song": "hf_song.json",
+    "song_index": "hf_song_indx.json"
+}
+
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class JJQA(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("0.0.1")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="qa", version=VERSION, description="This part of my dataset covers a first domain"),
+        datasets.BuilderConfig(name="song", version=VERSION, description="This part of my dataset covers a second domain"),
+        datasets.BuilderConfig(name="song_index", version=VERSION, description="This part of my dataset covers a first domain"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "qa"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
+        if self.config.name == "qa":  # This is the name of the configuration selected in BUILDER_CONFIGS above
+            description=_DESCRIPTION+" This is the field with Q&As."
+            features = datasets.Features(
+                {
+                    "q": datasets.Value("string"),
+                    "a": datasets.Value("string"),
+                    "rf": datasets.Value("string"),
+                    "song_title": datasets.Value("string"),
+                    "song_id": datasets.Value("string"),
+                    "id": datasets.Value("string"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+        elif self.config.name == "song":
+            description=_DESCRIPTION+" This is the field with songs."
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "name": datasets.Value("string"),
+                    "lyric": datasets.Value("string"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+            description=_DESCRIPTION+" This is the field with a song_id-index dict."
+            features = datasets.Features(
+                {   
+                    "dic": datasets.Value("string"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=description,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+            # supervised_keys=("sentence", "label"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": urls,
+                    # "split": "train",
+                },
+            )
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath):
+        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+        tmp=None
+        with open(filepath, encoding="utf-8") as f:
+            tmp=json.load(f)["data"]
+        if(self.config.name=="qa"):
+            for key, row in enumerate(tmp):
+                yield key, {
+                    "q": row["q"],
+                    "a": row["a"],
+                    "rf": row["rf"],
+                    "song_title": row["song_title"],
+                    "song_id": row["song_id"],
+                    "id": row["id"],
+                }
+        elif(self.config.name=="song"):
+            for key, row in enumerate(tmp):
+                yield key, {
+                    "id": row["id"],
+                    "title": row["title"],
+                    "name": row["name"],
+                    "lyric": row["lyric"],
+                }
+        else:
+            yield 0,{
+                "dic":json.dumps(tmp)
+            }

README.md

@@ -1,3 +1,49 @@
 ---
-license: apache-2.0
+dataset_info:
+- config_name: qa
+  features:
+  - name: q
+    dtype: string
+  - name: a
+    dtype: string
+  - name: rf
+    dtype: string
+  - name: song_title
+    dtype: string
+  - name: song_id
+    dtype: string
+  - name: id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 67824
+    num_examples: 648
+  download_size: 134589
+  dataset_size: 67824
+- config_name: song
+  features:
+  - name: id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: name
+    dtype: string
+  - name: lyric
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 253605
+    num_examples: 181
+  download_size: 276024
+  dataset_size: 253605
+- config_name: song_index
+  features:
+  - name: dic
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2872
+    num_examples: 1
+  download_size: 4168
+  dataset_size: 2872
 ---

hf_song_indx.json

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+{
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+}